The aim of realistic digital imaging is the creation of high quality imagery, which faithfully represents the physical
environment. The ultimate goal is to create images, which are perceptually indistinguishable from a real scene....
The aim of realistic digital imaging is the creation of high quality imagery, which faithfully represents the physical
environment. The ultimate goal is to create images, which are perceptually indistinguishable from a real scene. The
RealVision network brings together leading universities, centers focused on industrial development and companies in
Multimedia, Optics, Visual Communication, Visual Computing, Computer Graphics and Human Vision research across
Europe, with the aim of training a new generation of scientists, technologists, and entrepreneurs that will move Europe into a
leading role in innovative hyper-realistic imaging technologies. Current imaging technologies capture only a fraction of visual
information that the human eye can see. The colours and dynamic range are inadequate for most real-world scenes and not
all depth cues required for natural 3D vision are captured. This limits the realism of the experience and has hampered the
introduction of 3D technology. Advancement in imaging technologies makes it possible to circumvent these bottlenecks in
visual systems. As a result, new visual signal-processing areas have emerged such as light fields, ultra-high definition,
highframe
rate and high dynamic range imaging. The novel combinations of those technologies can facilitate a hyper-realistic
visual experience. This will without doubt be the future frontier for new imaging systems. However there are several
technological barriers that need to be overcome as well as challenges in what are the best solutions perceptually. The goal
of this network is to combine expertise from several disciplines as engineering, computer science, physics, vision science
and psychology – usually disconnected – and train ESRs to be capable of working with all stages and aspects of visual
processing to overcome existing interdisciplinary and intersectorial barriers to efficiently develop truly perceptually better
visual imaging systems.ver más
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